This is a GitHub Repository (repo for short) that supports teaching of the Transport Data Science module at the University of Leeds. The module can be taken by students on the Data Science and Analytics and (from 2022 onwards) Transport Planning and the Environment MSc courses.

The module catalogue can be found at catalogue.md. The computer code accompanying the course can be found in the code folders. To run this code you will need R and Python installed plus various packages and libraries.

The timetable can be found:

• On the University’s system (official): http://timetable.leeds.ac.uk/
• In ical format (for import into Google/Outlook/other Calendar systems): https://github.com/ITSLeeds/TDS/raw/master/timetable-2020.ics
• As a .csv file (for easy reading as data): https://github.com/ITSLeeds/TDS/blob/master/timetable-2020.csv

See below for the sessions

The module timetable is shown in the table below.

For this module you need to have up-to-date versions of R and RStudio. Install:

• R from cran.r-project.org
• RStudio from rstudio.com
• R packages, by opening RStudio and typing install.packages("stats19") in the R console.

We recommend using at least the latest stable release of R (4.0.0 or above). We recommend running R on a decent computer, with at least 4 GB RAM and ideally 8 GB or more RAM. See Section 1.5 of the online guide Reproducible Road Safety Research with R for instructions on how to install key packages we will use in the module.[1]

Slides can be found online:

• See https://itsleeds.github.io/TDS/slides/1-intro.html#1 for the introductory slides, for example
• Videos of the lectures can be found on the University of Leeds’ Blackboard system (you must must register to courses such as Data Science and Analytics or Transport Planning and the Environment to take the course)

• You will build-up a portfolio of work
• 100% coursework assessed, you will submit by Friday 14th May:
  • a pdf document up to 10 pages long with figures, tables, references explaining how you used data science to research a transport problem
  • reproducible code contained in an RMarkdown (.Rmd) document that produced the report
• Written in RMarkdown - will be graded for reproducibility
• Code chunks and figures are encouraged
• You will submit a non-assessed 2 page pdf + Rmd report by Friday 26th March

Any feedback or contributions to this repo are welcome. If you have a question please open an issue here (you’ll need a GitHub account): https://github.com/ITSLeeds/TDS/issues

[1] For further guidance on setting-up your computer to run R and RStudio for spatial data, see these links, we recommend Chapter 2 of Geocomputation with R (the Prerequisites section contains links for installing spatial software on Mac, Linux and Windows): https://geocompr.robinlovelace.net/spatial-class.html and Chapter 2 of the online book Efficient R Programming, particularly sections 2.3 and 2.5, for details on R installation and set-up and the project management section.